3S多线程处理与模糊c均值法的比较

D. Mortazavi, S. Mashohor, R. Mahmud, A. Jantan
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引用次数: 1

摘要

本文实现了医学图像强度分割的3S(缩水搜索空间)多阈值分割方法,并以分割质量和分割时间作为阈值分割的基准,与FCM方法进行了比较。结果表明,3S方法的分割质量与FCM方法几乎相同,甚至在某些情况下比FCM方法的分割质量更好,而且3S方法的计算时间远低于FCM方法。这是这种方法相对于其他方法的另一个优点。此外,还将C-means的性能与其他两种方法进行了比较。这个比较表明,C-means不是一个可靠的聚类算法,它需要多次运行才能给出一个可靠的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of 3S multi-thresolding with fuzzy C-means method
The 3S (Shrinking-Search-Space) multi-thresholding method which have been used for segmentation of medical images according to their intensities, now have been implemented and compared with FCM method in terms of segmentation quality and segmentation time as a benchmark in thresholding. The results show that 3S method produced almost the same segmentation quality or in some occasions better quality than FCM, and the computation time of 3S method is much lower than FCM. This is another superiority of this method with respect to others. Also, the performance of C-means has been compared with two other methods. This comparison shows that, C-means is not a reliable clustering algorithm and it needs several run to give us a reliable result.
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